ReviewTrends in cognitive sciences2020
The Child as Hacker.
Review in Trends in cognitive sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
20 citing papers in PubMed.
- Children use algorithm induction to discover patterns in data.Nature communications · 2026Article
- People Evaluate Agents Based on the Algorithms That Drive Their Behavior.Open mind : discoveries in cognitive science · 2025Article
- Seeking New Information With Old Questions: Children and Adults Reuse and Recombine Concepts From Prior Questions.Open mind : discoveries in cognitive science · 2025Article
- Building machines that learn and think with people.Nature human behaviour · 2024Review
- Symbolic metaprogram search improves learning efficiency and explains rule learning in humans.Nature communications · 2024Article
- Review
- Motor adaptation is reduced by symbolic compared to sensory feedback.bioRxiv : the preprint server for biology · 2024Article
- Review
- Response to Difficulty Drives Variation in IQ Test Performance.Open mind : discoveries in cognitive science · 2024Article
- A model of conceptual bootstrapping in human cognition.Nature human behaviour · 2024Article
- Developmental changes in exploration resemble stochastic optimization.Nature human behaviour · 2023Article
- Emotion prediction as computation over a generative theory of mind.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2023Article
- Embodied cognitive morphogenesis as a route to intelligent systems.Interface focus · 2023Article
- Darwin's agential materials: evolutionary implications of multiscale competency in developmental biology.Cellular and molecular life sciences : CMLS · 2023Review
- Eight-Month-Old Infants Meta-Learn by Downweighting Irrelevant Evidence.Open mind : discoveries in cognitive science · 2023Article
- The cultural origins of symbolic number.Psychological review · 2022Article
- Reply to Murphy and Leivada: Program induction can learn language.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Logical word learning: The case of kinship.Psychonomic bulletin & review · 2022Review
- One model for the learning of language.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- The computational origin of representation.Minds and machines · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
The scope of human learning and development poses a radical challenge for cognitive science. We propose that developmental theories can address this challenge by adopting perspectives from computer science. Many of our best models treat learning as analogous to computer programming because symbolic programs provide the most compelling account of sophisticated mental representations. We specifically propose that children's learning is analogous to a particular style of programming called hacking, making code better along many dimensions through an open-ended set of goals and activities. By contrast to existing theories, which depend primarily on local search and simple metrics, this view highlights the many features of good mental representations and the multiple complementary processes children use to create them.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.